Zobrazeno 1 - 10
of 6 805
pro vyhledávání: '"Bonaventure, A."'
Autor:
Tonja, Atnafu Lambebo, Dossou, Bonaventure F. P., Ojo, Jessica, Rajab, Jenalea, Thior, Fadel, Wairagala, Eric Peter, Aremu, Anuoluwapo, Moiloa, Pelonomi, Abbott, Jade, Marivate, Vukosi, Rosman, Benjamin
High-resource language models often fall short in the African context, where there is a critical need for models that are efficient, accessible, and locally relevant, even amidst significant computing and data constraints. This paper introduces Inkub
Externí odkaz:
http://arxiv.org/abs/2408.17024
Autor:
Dossou, Bonaventure F. P.
The Deep Learning revolution has enabled groundbreaking achievements in recent years. From breast cancer detection to protein folding, deep learning algorithms have been at the core of very important advancements. However, these modern advancements a
Externí odkaz:
http://arxiv.org/abs/2401.15721
In this work, we analyzed theoretically and experimentally the nonlinear dynamics of a magnetic pendulum driven by a coil-magnet interaction. The force between the magnetic elements and the resulting torque on the pendulum are derived using both the
Externí odkaz:
http://arxiv.org/abs/2401.10957
Autor:
Michel, François, Bonaventure, Olivier
The SSH protocol was designed in the late nineties to cope with the security problems of the telnetf family of protocols. It brought authentication and confidentiality to remote access protocols and is now widely used. Almost 30 years after the initi
Externí odkaz:
http://arxiv.org/abs/2312.08396
Autor:
Olatunji, Tobi, Afonja, Tejumade, Yadavalli, Aditya, Emezue, Chris Chinenye, Singh, Sahib, Dossou, Bonaventure F. P., Osuchukwu, Joanne, Osei, Salomey, Tonja, Atnafu Lambebo, Etori, Naome, Mbataku, Clinton
Africa has a very low doctor-to-patient ratio. At very busy clinics, doctors could see 30+ patients per day -- a heavy patient burden compared with developed countries -- but productivity tools such as clinical automatic speech recognition (ASR) are
Externí odkaz:
http://arxiv.org/abs/2310.00274
Multicast enables efficient one-to-many communications. Several applications benefit from its scalability properties, e.g., live-streaming and large-scale software updates. Historically, multicast applications have used specialized transport protocol
Externí odkaz:
http://arxiv.org/abs/2309.06633
Autor:
Piraux, Maxime, Bonaventure, Olivier
Latency is becoming a key factor of performance for Internet applications and has triggered a number of changes in its protocols. Our work revisits the impact on latency of address family selection in dual-stack hosts. Through RIPE Atlas measurements
Externí odkaz:
http://arxiv.org/abs/2309.05369
The Fon language, spoken by an average 2 million of people, is a truly low-resourced African language, with a limited online presence, and existing datasets (just to name but a few). Multitask learning is a learning paradigm that aims to improve the
Externí odkaz:
http://arxiv.org/abs/2308.14280
Autor:
Houcemeddine Turki, Bonaventure F. P. Dossou, Chris Chinenye Emezue, Abraham Toluwase Owodunni, Mohamed Ali Hadj Taieb, Mohamed Ben Aouicha, Hanen Ben Hassen, Afif Masmoudi
Publikováno v:
Journal of Biomedical Semantics, Vol 15, Iss 1, Pp 1-28 (2024)
Abstract Biomedical relation classification has been significantly improved by the application of advanced machine learning techniques on the raw texts of scholarly publications. Despite this improvement, the reliance on large chunks of raw text make
Externí odkaz:
https://doaj.org/article/17730408430a4d3fa54beb1284027b36
Autor:
Emmanuel Kokori, Gbolahan Olatunji, Rosemary Komolafe, Ikponmwosa Jude Ogieuhi, Bonaventure Ukoaka, Irene Ajayi, Nicholas Aderinto
Publikováno v:
Clinical Diabetes and Endocrinology, Vol 10, Iss 1, Pp 1-6 (2024)
Abstract Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder affecting women of reproductive age, characterised by its multifactorial nature and intricate interplay of genetic, hormonal, and environmental factors. As the search for rel
Externí odkaz:
https://doaj.org/article/a9fa606252414a0d98f77d788414818f